July 2022 arXiv papers — page 92

P. C. Bhat, S. Belomestnykh, A. Bross, S. Dasu

Future colliders are an essential component of a strategic vision for particle physics. Conceptual studies and technical developments for several exciting future collider options are underway internationally. In order to realize a future collider, a concerted accelerator R\&D program is required. The U.S. HEP accelerator R\&D program currently has no direct

Qiongqiong Pan

We prove a combinatorial formula for the alternating descent polynomials of type A and B. Combining with Josuat-Verg\`es' combinatorial interpretation for Hoffman's derivative polynomials for tangent and secant functions, we obtain a unified combinatorial proof of Ma-Yeh's two formulae linking these two families of polynomials.

Tom Joy, Francesco Pinto, Ser-Nam Lim, Philip H. S. Torr

It is now well known that neural networks can be wrong with high confidence in their predictions, leading to poor calibration. The most common post-hoc approach to compensate for this is to perform temperature scaling, which adjusts the confidences of the predictions on any input by scaling the logits by a fixed value. Whilst this approach typically improves

Agi Kurucz, Vladislav Ryzhikov, Yury Savateev, Michael Zakharyaschev

Our concern is the problem of determining the data complexity of answering an ontology-mediated query (OMQ) formulated in linear temporal logic LTL over (Z,<) and deciding whether it is rewritable to an FO(<)-query, possibly with some extra predicates. First, we observe that, in line with the circuit complexity and FO-definability of regular languages, OMQ a

Hannah He, Joe Norby, Sean Wang, Natasha Sihota

The automation of data collection via mobile robots holds promise for increasing the efficacy of environmental investigations, but requires the system to autonomously determine how to sample the environment while avoiding obstacles. Existing methods such as the boustrophedon decomposition algorithm enable complete coverage of the environment to a specified r

Jinxin Xue

In this paper, we develop an approach to the problem of closing lemma based on KAM normal form. The new approach differs from existing $C^1$ perturbation approach and spectral approach, and can handle the high regularity, high dimensional cases and even Riemannian metric perturbations. Moreover, the proof is constructive and effective. We apply the method to

Janus Collaboration, M. Baity-Jesi, E. Calore, A. Cruz

Memory and rejuvenation effects in the magnetic response of off-equilibrium spin glasses have been widely regarded as the doorway into the experimental exploration of ultrametricity and temperature chaos (maybe the most exotic features in glassy free-energy landscapes). Unfortunately, despite more than twenty years of theoretical efforts following the experi

L. Schena, E. Gillyns, W. Munters, S. Buckingham

This article presents two model-free controllers for wind-turbine torque and pitch control. These controllers are based on reinforcement learning (RL) and Bayesian optimization (BO) and do not rely on any mathematical model of the wind-turbine dynamics, in contrast to classical approaches designed on linearized models. The model-free controllers were benchma

Chang Chen, Jiaming Zhang, Kailun Yang, Kunyu Peng

Humans have an innate ability to sense their surroundings, as they can extract the spatial representation from the egocentric perception and form an allocentric semantic map via spatial transformation and memory updating. However, endowing mobile agents with such a spatial sensing ability is still a challenge, due to two difficulties: (1) the previous convol

D. G. Duarte, L. B. de Oliveira, F. S. Nascimento, W. A. Moura-Melo

Magnetic monopole unpairing as a function of external magnetic fields is presented as a fingerprint of this emergent quasiparticles freedom in a two-dimensional artificial spin ice system. Such freedom, required for example for further application in magnetricity, is only possible due to ground-state degeneracy, which causes a decreasing of the string energy

Ryosuke Kobashi, Haruo Yasuda, Shiu-Hang Lee

The contribution of galactic supernova remnants (SNRs) to the origin of cosmic rays (CRs) is an important open question in modern astrophysics. Broadband non-thermal emission is a useful proxy for probing the energy budget and production history of CRs in SNRs. We conduct hydrodynamic simulations to model the long-term SNR evolution from explosion all the wa

Ziyi Dong, Pengxu Wei, Liang Lin

Object detection, as a fundamental computer vision task, has achieved a remarkable progress with the emergence of deep neural networks. Nevertheless, few works explore the adversarial robustness of object detectors to resist adversarial attacks for practical applications in various real-world scenarios. Detectors have been greatly challenged by unnoticeable

Yu Zhang, Ying-Wen He, D. Karlsson, Chong Qi

The anomalous low-energy $E2$-related behavior of a triaxially-deformed nucleus bas been identified and analyzed based on the SU(3) algebraic theory within the framework of the interacting boson model. The results show striking features that include a $B(E2;4_1^+\rightarrow2_1^+)/B(2_1^+\rightarrow0_1^+)<1.0$ transition rate ratio and a $E(4_1^+)/E(2_1^+)>2.

Guilai Liu, Chengming Bai

Anti-pre-Lie algebras, Novikov algebras and commutative 2-cocycles on Lie algebrasWe introduce the notion of anti-pre-Lie algebras as the underlying algebraic structures of nondegenerate commutative 2-cocycles which are the "symmetric" version of symplectic forms on Lie algebras. They can be characterized as a class of Lie-admissible algebras whose negative

Cynthia Chen, Bruno Schmitt, Helena Zhang, Lev S. Bishop

We describe a family of recursive methods for the synthesis of qubit permutations on quantum computers with limited qubit connectivity. Two objectives are of importance: circuit size and depth. In each case we combine a scalable heuristic with a non-scalable, yet exact, synthesis. Our algorithms are applicable to generic connectivity constraints, scale favor

Shubham Sharma, Amruta Desai, Prince A. Ganai

We examine the effect of addition of graviton mass on the efficiency of a regular charged black hole (RCB). In doing so, we make few comments on the critical behaviour of the system and calculate the relevant thermodynamic quantities such as entropy, Hawkings temperature and heat capacity. We confirm that graviton mass has a positive effect on the efficacy o

Biplab Paul, Abhishek Saha

We investigate some key analytic properties of Fourier coefficients and Hecke eigenvalues attached to scalar-valued Siegel cusp forms $F$ of degree 2, weight $k$ and level $N$. First, assuming that $F$ is a Hecke eigenform that is not of Saito-Kurokawa type, we prove an improved bound in the $k$-aspect for the smallest prime at which its Hecke eigenvalue is

Innes Bigaran, Tobias Felkl, Claudia Hagedorn, Michael A. Schmidt

We construct an extension of the Standard Model with a scalar leptoquark $\phi \sim (3,1,-\tfrac13)$ and the discrete flavour symmetry $G_f=D_{17}\times Z_{17}$ to explain anomalies observed in charged-current semi-leptonic $B$ meson decays and in the muon anomalous magnetic moment, together with the charged fermion masses and quark mixing. The symmetry $Z_{

Natnael A. Wondimu, Cédric Buche, Ubbo Visser

Machine learning has proved useful in many software disciplines, including computer vision, speech and audio processing, natural language processing, robotics and some other fields. However, its applicability has been significantly hampered due its black-box nature and significant resource consumption. Performance is achieved at the expense of enormous compu

Luca Donati, Marcus Weber

We present a method to estimate the transition rates of molecular systems under different environmental conditions which cause the formation or the breaking of bonds and require the sampling of the Grand Canonical Ensemble. For this purpose, we model the molecular system in terms of probable "scenarios", governed by different potential energy functions, whic

Nunzio Dimola, Alessandro Coclite, Giuseppe Fanizza, Tiziano Politi

Peridynamic (PD) theories have gained widespread diffusion among various research areas, due to the ability of modeling discontinuities formation and evolution in materials. Bond-Based Peridynamics (BB-PD), notwithstanding some modeling limitations, is widely employed in numerical simulations, due to its easy implementation combined with physical intuitivene

Péter Bándi, Maschenka Balkenhol, Marcory van Dijk, Bram van Ginneken

Recently, large, high-quality public datasets have led to the development of convolutional neural networks that can detect lymph node metastases of breast cancer at the level of expert pathologists. Many cancers, regardless of the site of origin, can metastasize to lymph nodes. However, collecting and annotating high-volume, high-quality datasets for every c

Sudip Ranjan Bhuia, Deepak Pradhan, Jaydeb Sarkar

We present complete characterizations of Toeplitz operators that are complex symmetric. This follows as a by-product of characterizations of conjugations on Hilbert spaces. Notably, we prove that every conjugation admits a canonical factorization. As a consequence, we prove that a Toeplitz operator is complex symmetric if and only if the Toeplitz operator is

Gordon Blower

The paper proves transportation inequalities for probability measures on spheres for the Wasserstein metrics with respect to cost functions that are powers of the geodesic distance. Let $\mu$ be a probability measure on the sphere ${\bf S}^n$ of the form $d\mu =e^{-U(x)}dx$ where $dx$ is the rotation invariant probability measure, and $(n-1)I+{\hbox{Hess}}\,

Jinho Choo, Yeong-Dae Kwon, Jihoon Kim, Jeongwoo Jae

Neural approaches for combinatorial optimization (CO) equip a learning mechanism to discover powerful heuristics for solving complex real-world problems. While neural approaches capable of high-quality solutions in a single shot are emerging, state-of-the-art approaches are often unable to take full advantage of the solving time available to them. In contras

Ziyi Shen, Qianye Yang, Yuming Shen, Francesco Giganti

Image registration is useful for quantifying morphological changes in longitudinal MR images from prostate cancer patients. This paper describes a development in improving the learning-based registration algorithms, for this challenging clinical application often with highly variable yet limited training data. First, we report that the latent space can be cl

Ryan Li, Joshua Studholme, Alexey Fedorov, Trude Storelvmo

Cloud processes are the largest source of uncertainty in quantifying the global temperature response to carbon dioxide rise. Still, the role of precipitation efficiency (PE) -- surface rain per unit column -- integrated condensation -- is yet to be quantified. Here we use 36 limited-domain cloud resolving simulations from the Radiative-Convective Equilibrium

Konrad J. Kapcia, Victor Tkachenko, Flavio Capotondi, Alexander Lichtenstein

Magnetization dynamics triggered with ultrashort laser pulses has been attracting significant attention, with strong focus on the dynamics excited by VIS/NIR pulses. Only recently, strong magnetic response in solid materials induced by intense X-ray pulses from free-electron lasers (FELs) has been observed. The exact mechanisms that trigger the X-ray induced

H. Korbmacher, P. Sierant, W. Li, X. Deng

Inter-site interactions in polar lattice gases may result, due to Hilbert-space fragmentation, in a lack of ergodicity even in absence of disorder. We show that the inter-site interaction in a one-dimensional dipolar gas in an optical lattice departs from the usually considered $1/r^3$ dependence, acquiring a universal form that depends on the transversal co

Lauri Vähä-Savo, Katsuyuki Haneda, Clemens Icheln, Xiaoshu Lü

The importance of indoor mobile connectivity has increased during the last years, especially during the Covid-19 pandemic. In contrast, new energy-efficient buildings contain structures like low-emissive windows and multi-layered thermal insulations which all block radio signals effectively. To solve this problem with indoor connectivity, we study passive an

Emilien Zabeth

We give a new proof for the description of the blocks in the category of representations of a reductive algebraic group $\mathbf{G}$ over a field of positive characteristic $\ell$ (originally due to Donkin), by working in the Satake category of the Langlands dual group and applying Smith-Treumann theory as developed by Riche and Williamson. On the representa

Gor Safaryan, Anshul Jindal, Mohak Chadha, Michael Gerndt

Serverless computing paradigm has become more ingrained into the industry, as it offers a cheap alternative for application development and deployment. This new paradigm has also created new kinds of problems for the developer, who needs to tune memory configurations for balancing cost and performance. Many researchers have addressed the issue of minimizing

Mark Quinlan, Jun Zhao, Andrew Simpson

Just as the world of consumer devices was forever changed by the introduction of computer controlled solutions, the introduction of the engine control unit (ECU) gave rise to the automobile's transformation from a transportation product to a technology platform. A modern car is capable of processing, analysing and transmitting data in ways that could not hav

Peng Song, Mari Kawaguchi, Yuji Masubuchi, Kenji Oqmhula

Polymers containing nitrogen have attracted much attention in connection with their application to high energy density materials (HEDMs), in which energy is inherent in the triple bond. It is an interesting question whether such polymerized phases appear in the high-pressure phase of metal carbodiimide MCN$_2$, of which synthesis have been reported in recent

Ping-Cheng Wei, Kunyu Peng, Alina Roitberg, Kailun Yang

Failure to timely diagnose and effectively treat depression leads to over 280 million people suffering from this psychological disorder worldwide. The information cues of depression can be harvested from diverse heterogeneous resources, e.g., audio, visual, and textual data, raising demand for new effective multi-modal fusion approaches for automatic estimat

Jonathan Morag, Nir Sapir, Eli Waxman

Supernova light curves are dominated at early time, hours to days, by the escape of photons from the expanding shock heated envelope. We provide a simple analytic description of the time dependent luminosity, $L$, and color temperature, $T_{\rm col}$, for explosions of red supergiants (with convective polytropic envelopes), valid up to H recombination ($T\ap

Weideng Cui

We provide a combinatorial characterization of two-sided cells in modified $\imath$quantum groups of type AIII. Our approach is to lift a corresponding description of two-sided cells in $\jmath$-Schur algebras associated to Iwahori--Hecke algebras of type $B$. We further give a combinatorial description of two-sided cells in other two kinds of Schur-type alg

Yiting Lu, Jun Fu, Xin Li, Wei Zhou

Coronary CT Angiography (CCTA) is susceptible to various distortions (e.g., artifacts and noise), which severely compromise the exact diagnosis of cardiovascular diseases. The appropriate CCTA Vessel-level Image Quality Assessment (CCTA VIQA) algorithm can be used to reduce the risk of error diagnosis. The primary challenges of CCTA VIQA are that the local p

Xin Zhou, Chao Xu, Fei Gao

Online trajectory planners enable quadrotors to safely and smoothly navigate in unknown cluttered environments. However, tuning parameters is challenging since modern planners have become too complex to mathematically model and predict their interaction with unstructured environments. This work takes humans out of the loop by proposing a planner parameter ad

Evelyn Diaz-Escobar, Angela I. Barreda, Amadeu Griol, Alejandro Martinez

Anapole states - characterized by a strong suppression of far-field scattering - naturally arise in high-index nanoparticles as a result of the interference between certain multipolar moments. Recently, the first-order electric anapole, resulting from the interference between the electric and toroidal dipoles, was characterized under in-plane illumination as

Fabrizio Di Giovanni, Davide Guerra, Simone Albanesi, Miquel Miravet-Tenés

We construct spherically-symmetric static solutions of the Einstein-Klein-Gordon-Euler system involving a complex scalar field governed by a periodic potential which emerges in models of axion-like particles, and fermionic matter modeled by a perfect fluid with a polytropic equation of state. Such solutions describe gravitationally bound composites of fermio

B. Vollmer, M. Soida, J. Dallant

Given the multiple energy loss mechanisms of cosmic ray electrons in galaxies, the tightness of the infrared - radio continuum correlation is surprising. We extended the analytical model of galactic disks of Vollmer et al. (2017) by including a simplified prescription for the synchrotron emissivity. The galactic gas disks of local spiral galaxies, low-z star

Ovidiu Iacoboaiea, Jonatan Krolikowski, Zied Ben Houidi, Dario Rossi

Machine learning (ML) is increasingly used to automate networking tasks, in a paradigm known as zero-touch network and service management (ZSM). In particular, Deep Reinforcement Learning (DRL) techniques have recently gathered much attention for their ability to learn taking complex decisions in different fields. In the ZSM context, DRL is an appealing cand

Keisuke Miyamoto

We can run the MMP for any divisor on any $\mathbb{Q}$-factorial projective toric variety. We show that two Mori fiber spaces, which are outputs of the above MMP, are connected by finitely many elementary transforms.

Beomseok Kang, Harshit Kumar, Saurabh Dash, Saibal Mukhopadhyay

Learning the evolution of real-time strategy (RTS) game is a challenging problem in artificial intelligent (AI) system. In this paper, we present a novel Hebbian learning method to extract the global feature of point sets in StarCraft II game units, and its application to predict the movement of the points. Our model includes encoder, LSTM, and decoder, and

Uwe Naumann

Adjoint algorithmic differentiation by operator and function overloading is based on the interpretation of directed acyclic graphs resulting from evaluations of numerical simulation programs. The size of the computer system memory required to store the graph grows proportional to the number of floating-point operations executed by the underlying program. It

Mohsen Gheibi

Following our previous work about quasi-projective dimension, in this paper, we introduce quasi-injective dimension as a generalization of injective dimension. We recover several well-known results about injective and Gorenstein-injective dimensions in the context of quasi-injective dimension such as the following. (a) If the quasi-injective dimension of a f

Aishrila Mazumder, Abhirup Datta, Arnab Chakraborty, Suman Majumdar

Observation of the redshifted 21-cm signal from Cosmic Dawn and Epoch of Reionization is a challenging endeavor in observational cosmology. Presence of orders of magnitude brighter astrophysical foregrounds and various instrumental systematics increases the complexity of these observations. This work presents an end-to-end pipeline dealing with synthetic int

Zifu Wang, Matthew B. Blaschko

UNet [27] is widely used in semantic segmentation due to its simplicity and effectiveness. However, its manually-designed architecture is applied to a large number of problem settings, either with no architecture optimizations, or with manual tuning, which is time consuming and can be sub-optimal. In this work, firstly, we propose Markov Random Field Neural

Bo Pang, Yifan Zhang, Yaoyi Li, Jia Cai

In this paper, we propose a genuine group-level contrastive visual representation learning method whose linear evaluation performance on ImageNet surpasses the vanilla supervised learning. Two mainstream unsupervised learning schemes are the instance-level contrastive framework and clustering-based schemes. The former adopts the extremely fine-grained instan

Pranay Seshadri, Andrew B. Duncan, George Thorne, Raul Vazquez Diaz

This manuscript outlines an automated anomaly detection framework for jet engines. It is tailored for identifying spatial anomalies in steady-state temperature measurements at various axial stations in an engine. The framework rests upon ideas from optimal transport theory for Gaussian measures which yields analytical solutions for both Wasserstein distances

Timothy Y. Chow

Some Christian apologists, notably William Lane Craig, have championed something called the kalam cosmological argument for the existence of God. One version of the argument leans heavily on the claim that the existence of an actual infinite in the physical world is a metaphysical impossibility. We strongly criticize this claim, showing that it involves dogm

Demetrios A. Pliakis

I prove the existence of small time heat expansion for the Laplace operator on an analytic hypersurface with an isolated singularity. First we obtain a local parametrization of the hypersurface near the singularity. We introduce the notion of quasihomogeneous tangent cone. Then perturb the parametrization of the cone employing a Newton scheme and obtain a pa

Dominik Vietinghoff, Michael Böttinger, Gerik Scheuermann, Christian Heine

An important task in visualization is the extraction and highlighting of dominant features in data to support users in their analysis process. Topological methods are a well-known means of identifying such features in deterministic fields. However, many real-world phenomena studied today are the result of a chaotic system that cannot be fully described by a

Christophe Gomez

This work concerns the asymptotic analysis of high-frequency wave propagation in randomly layered media with fast variations and long-range correlations. The analysis takes place in the 3D physical space and weak-coupling regime. The role played by the slow decay of the correlations on a propagating pulse is two fold. First we observe a random travel time ch

Georgios Korpas

We review holographic renormalization for non-conformal branes using the Hamilton-Jacobi formalism. We provide the tools required for the computation of the holographic dictionary, while we present some marginally new technical results regarding holographic renormalization for $Dp$-branes, $p<5$, for Einstein-Maxwell theory coupled to a dilaton. The computat

Jaron Kent-Dobias, Jorge Kurchan

We derive the general solution for counting the stationary points of mean-field complex landscapes. It incorporates Parisi's solution for the ground state, as it should. Using this solution, we count the stationary points of two models: one with multi-step replica symmetry breaking, and one with full replica symmetry breaking.

Athanasios Tsintzis, Rubén Seoane Souto, Martin Leijnse

We propose and theoretically investigate an alternative way to create the poor man's Majorana bound states (MBSs) introduced in Phys. Rev. B 86, 134528 (2012). Our proposal is based on two quantum dots (QDs) with strong electron-electron interactions that couple via a central QD with proximity-induced superconductivity. In the presence of spin-orbit coupling

Yifan Wu, Michael B. Wakin, Peter Gerstoft

Direction-of-arrival (DOA) estimation is widely applied in acoustic source localization. A multi-frequency model is suitable for characterizing the broadband structure in acoustic signals. In this paper, the continuous (gridless) DOA estimation problem with multiple frequencies is considered. This problem is formulated as an atomic norm minimization (ANM) pr

Alexei A. Mailybaev, Artem Raibekas

We introduce a class of multi-scale systems with discrete time, motivated by the problem of inviscid limit in fluid dynamics in the presence of small-scale noise. These systems are infinite-dimensional and defined on a scale-invariant space-time lattice. We propose a qualitative theory describing the vanishing regularization (inviscid) limit as an attractor

J. P. Hadden, Cobi Maynard, Daryl M. Beggs, Robert A. Taylor

Photonic waveguides with triangular cross section are being investigated for material systems such as diamond, glasses and gallium nitride, which lack easy options to create conventional rectangular nanophotonic waveguides. The design rules for optical elements in these triangular waveguides, such as couplers and gratings, are not well established. Here we p

Ángel F. García-Fernández, Yuxuan Xia, Lennart Svensson

This paper provides a comparative analysis between the adaptive birth model used in the labelled random finite set literature and the track initiation in the Poisson multi-Bernoulli mixture (PMBM) filter, with point-target models. The PMBM track initiation is obtained via Bayes' rule applied on the predicted PMBM density, and creates one Bernoulli component

Tiziana Calamoneri, Federico Corò, Simona Mancini

Unmanned aerial vehicles (UAVs) are aircraft whose flights can be fully autonomous without any provision for human intervention. One of the most useful and promising domains where UAVs can be employed is natural disaster management. In this paper, we focus on an emergency scenario and propose the use of a fleet of UAVs that help rescue teams to individuate p

Rohit Shaw

The growing adoption of IoT devices for healthcare has enabled researchers to build intelligence using all the data produced by these devices. Monitoring and diagnosing health have been the two most common scenarios where such devices have proven beneficial. Achieving high prediction accuracy was a top priority initially, but the focus has slowly shifted to

Luca Bortolussi, Ginevra Carbone, Luca Laurenti, Andrea Patane

Vulnerability to adversarial attacks is one of the principal hurdles to the adoption of deep learning in safety-critical applications. Despite significant efforts, both practical and theoretical, training deep learning models robust to adversarial attacks is still an open problem. In this paper, we analyse the geometry of adversarial attacks in the large-dat

Peter Mlkvik, Claude Ederer, Nicola A. Spaldin

We present a density-functional theory (DFT) study of the structural, electronic, and chemical bonding behaviour in germanium (Ge)-doped vanadium dioxide (VO$_2$). Our motivation is to explain the reported increase of the metal-insulator transition temperature under Ge doping and to understand how much of the fundamental physics and chemistry behind it can b

Carlos Ortega-Taberner, Antti-Pekka Jauho, Jens Paaske

Josephson junctions based on quantum dots offer a convenient tunability by means of local gates. Here we analyze a Josephson junction based on a serial double quantum dot in which the two dots are individually gated by phase-shifted microwave tones of equal frequency. We calculate the time-averaged current across the junction and determine how the phase shif

C. Zhong, F. J. Luo, B. Zheng, X. D. Wang

Radon is the main background source of dark matter and neutrino experiments. Radon concentration ($\rm mBq/m^3$) measurement by liquid scintillation detector is a highly sensitive method at low temperatures using silicon photomultipliers (SiPMs) arrays. The SiPM performance characteristics are closely related to the lower detection limit of the detector. In

Pedro Machado, Ivica Matic, Francisco de Lemos, Isibor Kennedy Ihianle

Modern-day life is driven by electronic devices connected to the internet. The emerging research field of the Internet-of-Things (IoT) has become popular, just as there has been a steady increase in the number of connected devices. Since many of these devices are utilised to perform CV tasks, it is essential to understand their power consumption against perf

James Richard Andrew Gray

The main purpose of this paper is to show that the converse of the known implication weakly action representable implies action accessible is false. In particular we show that both action accessibility, as well as the (at least formally stronger) condition requiring the existence of all normalizers do not imply weakly-action-representability even for varieti

Shankhanil Mitra, Rajiv Soundararajan

Completely blind video quality assessment (VQA) refers to a class of quality assessment methods that do not use any reference videos, human opinion scores or training videos from the target database to learn a quality model. The design of this class of methods is particularly important since it can allow for superior generalization in performance across vari

Fan Chen, Junyu Zhang, Zaiwen Wen

As an important framework for safe Reinforcement Learning, the Constrained Markov Decision Process (CMDP) has been extensively studied in the recent literature. However, despite the rich results under various on-policy learning settings, there still lacks some essential understanding of the offline CMDP problems, in terms of both the algorithm design and the

Lukas Wegmeth

Recent model-based Recommender Systems (RecSys) algorithms emphasize on the use of features, also called side information, in their design similar to algorithms in Machine Learning (ML). In contrast, some of the most popular and traditional algorithms for RecSys solely focus on a given user-item-rating relation without including side information. The goal of

L. Ramambason, V. Lebouteiller, A. Bik, C. T. Richardson

(abridged) Quantifying the ISM porosity to ionizing photons in nearby galaxies may improve our understanding of the mechanisms leading to Lyman Continuum photons leakage from galaxies. Primitive galaxies with low metal and dust content have been shown to host a more patchy and porous ISM than their high-metallicity counterparts. To what extent this peculiar

Moataz M. Alghamdi, Fleurianne Bertrand, Daniele Boffi, Francesca Bonizzoni

In this paper a novel numerical approximation of parametric eigenvalue problems is presented. We motivate our study with the analysis of a POD reduced order model for a simple one dimensional example. In particular, we introduce a new algorithm capable to track the matching of eigenvalues when the parameters vary.

Mohamed Taoufiq Damir, Tommi Meskanen, Sara Ramezanian, Valtteri Niemi

The standardized Authentication and Key Agreement protocol for 5G networks (5G AKA) have several security and privacy vulnerabilities. In this paper, we propose a novel authentication and key agreement protocol for 5G and beyond that is compatible with the standardized 5G AKA. Our protocol has several privacy and security properties, e.g., perfect forward se

Qianyun Miao, Fa Peng, Yuan Zhou

Let $\Omega\subset R^n$ be a bounded convex domain with $n\ge2$. Suppose that $A$ is uniformly elliptic and belongs to $W^{1,n}$ when $n\ge 3$ or $W^{1,q}$ for some $q>2$ when $n=2$. For $1<p<\infty$, we build up a global second order regularity estimate $$\|D[|Du|^{p-2} Du]\|_{L^2(\Omega)}+\|D[ |\sqrt{A}Du|^{p-2} A Du]\|_{L^2(\Omega)} \le C \|f\|_{L^2(\Omeg

Gianmarco Perrupato, Maria Chiara Angelini, Giorgio Parisi, Federico Ricci-Tersenghi

We investigate the replica symmetry broken (RSB) phase of spin glass (SG) models in a random field defined on Bethe lattices at zero temperature. From the properties of the RSB solution we deduce a closed equation for the extreme values of the cavity fields. This equation turns out not to depend on the parameters defining the RSB, and it predicts that the sp

Xiaoxiang Chai, Xueyuan Wan

Let $(M,g)$ be a complete connected $n$-dimensional Riemannian spin manifold without boundary such that the scalar curvature satisfies $R_g\geq -n(n-1)$ and $\mathcal{E}\subset M$ be an asymptotically hyperbolic end, we prove that the mass functional of the end $\mathcal{E}$ is timelike future-directed or zero. Moreover, it vanishes if and only if $(M,g)$ is

Wending Mai, Chunxu Mao, Galestan Mackertich-Sengerdy, Yifan Chen

Chiral structures have reported radiation of circular polarized electromagnetic waves (CPs) in a specific direction. Here we report a class of torus knot radiators that is not only chiral but also three-dimensional (3-D) rotational symmetric along X, Y and Z axes. Because of this exotic chirality and symmetry, the knot radiator presented is able to demonstra

Guangyao Xu, Junfeng Fan, En Li, Xiaoyu Long

Depth estimation is one of the key technologies in some fields such as autonomous driving and robot navigation. However, the traditional method of using a single sensor is inevitably limited by the performance of the sensor. Therefore, a precision and robust method for fusing the LiDAR and stereo cameras is proposed. This method fully combines the advantages

S. Rayaprol, K. K. Iyer, A. Hoser, M. Reehuis

There have been constant efforts to find exotic quantum spin-liquid (QSL) materials. Some of the transition metal insulators dominated by the direction dependent anisotropic exchange interaction (Kitaev model for honeycomb network of magnetic ions) are considered to be promising cases for the same. In such Kitaev insulators, QSL is achieved from the zero-fie

Joanna Sliwa, Shubhangi Ghosh, Vincent Stimper, Luigi Gresele

One aim of representation learning is to recover the original latent code that generated the data, a task which requires additional information or inductive biases. A recently proposed approach termed Independent Mechanism Analysis (IMA) postulates that each latent source should influence the observed mixtures independently, complementing standard nonlinear

Marco A. Stranisci, Simona Frenda, Mirko Lai, Oscar Araque

Inside the NLP community there is a considerable amount of language resources created, annotated and released every day with the aim of studying specific linguistic phenomena. Despite a variety of attempts in order to organize such resources has been carried on, a lack of systematic methods and of possible interoperability between resources are still present

Jan Kruschewski, Farmer Schlutzenberg

We investigate Steel's conjecture in 'The Core Model Iterability Problem', that if $W$ and $R$ are $\Omega+1$-iterable, $1$-small weasels, then $W\leq^{*}R$ iff there is a club $C\subset\Omega$ such that for all $\alpha\in C$, if $\alpha$ is regular, then the cardinal successor of $\alpha$ in $W$ is less or equal than the cardinal successor of $\alpha$ in $R

Yuriel Nunez-Fernandez, Matthieu Jeannin, Philipp T. Dumitrescu, Thomas Kloss

We use tensor network techniques to obtain high order perturbative diagrammatic expansions for the quantum many-body problem at very high precision. The approach is based on a tensor train parsimonious representation of the sum of all Feynman diagrams, obtained in a controlled and accurate way with the tensor cross interpolation algorithm. It yields the full

Maximilian Engel, Felix Hummel, Christian Kuehn, Nikola Popović

We study a singularly perturbed fast-slow system of two partial differential equations (PDEs) of reaction-diffusion type on a bounded domain via Galerkin discretisation. We assume that the reaction kinetics in the fast variable realise a generic fold singularity, whereas the slow variable takes the role of a dynamic bifurcation parameter, thus extending the

Deyue Zhang, Yukun Guo, Yinglin Wang, Yan Chang

This paper concerns the simultaneous reconstruction of a sound-soft cavity and its excitation sources from the total-field data. Using the single-layer potential representations on two measurement curves, this co-inversion problem can be decoupled into two inverse problems: an inverse cavity scattering problem and an inverse source problem. This novel decoup

Anindya Goswami, Subhamay Saha, Ravishankar Kapildev Yadav

We consider a class of semi-Markov processes (SMP) such that the embedded discrete time Markov chain may be non-homogeneous. The corresponding augmented processes are represented as semi-martingales using stochastic integral equation involving a Poisson random measure. The existence and uniqueness of the equation are established. Subsequently, we show that t

Riccardo Marini, Sangwoo Park, Osvaldo Simeone, Chiara Buratti

Unmanned aerial base stations (UABSs) can be deployed in vehicular wireless networks to support applications such as extended sensing via vehicle-to-everything (V2X) services. A key problem in such systems is designing algorithms that can efficiently optimize the trajectory of the UABS in order to maximize coverage. In existing solutions, such optimization i

Jinyi Hu, Xiaoyuan Yi, Wenhao Li, Maosong Sun

The past several years have witnessed Variational Auto-Encoder's superiority in various text generation tasks. However, due to the sequential nature of the text, auto-regressive decoders tend to ignore latent variables and then reduce to simple language models, known as the KL vanishing problem, which would further deteriorate when VAE is combined with Trans

Yusuf Ramadana, Hendra Gunawan

In this paper we investigate the boundedness of classical operators, namely the Hardy-Littlewood maximal operator, fractional integral operators, and Calderon-Zygmund operators, on generalized weighted Morrey spaces and generalized weighted weak Morrey spaces. We prove that the operators are bounded on these spaces, under certain assumptions.

Wolfgang Dahmen

Approximating functions of a large number of variables poses particular challenges often subsumed under the term ``Curse of Dimensionality'' (CoD). Unless the approximated function exhibits a very high level of smoothness the CoD can be avoided only by exploiting some typically hidden {\em structural sparsity}. In this paper we propose a general framework fo

Xiangming Gu, Longshen Ou, Danielle Ong, Ye Wang

Automatic lyric transcription (ALT) is a nascent field of study attracting increasing interest from both the speech and music information retrieval communities, given its significant application potential. However, ALT with audio data alone is a notoriously difficult task due to instrumental accompaniment and musical constraints resulting in degradation of b

Eugene Bulyak, Viktor Mytrochenko, Iryna Chaikovska, Viacheslav Kubytskyi

The positrons produced with the electron beam impinging on a conversion target, possess wide energy spectrum and large sweep of the angle of trajectories to the system axis. Accommodation of the positron bunch to the acceptance of an ajacent accelerator, mandates the reduction of angular spread. One of the most appropriate devices for transforming the phase

Margarita Arias, Juan Campos

Analysis of the speed of propagation in parabolic operators is frequently carried out considering the minimal speed at which its traveling waves move. This value depends on the solution concept being considered. We analyze an extensive class of Fisher-type reaction-diffusion equations with flows in divergence form. We work with regular flows, which may not m

Songhua Liu, Jingwen Ye, Sucheng Ren, Xinchao Wang

One key challenge of exemplar-guided image generation lies in establishing fine-grained correspondences between input and guided images. Prior approaches, despite the promising results, have relied on either estimating dense attention to compute per-point matching, which is limited to only coarse scales due to the quadratic memory cost, or fixing the number

Pietro Mazzaglia, Tim Verbelen, Ozan Çatal, Bart Dhoedt

The free energy principle, and its corollary active inference, constitute a bio-inspired theory that assumes biological agents act to remain in a restricted set of preferred states of the world, i.e., they minimize their free energy. Under this principle, biological agents learn a generative model of the world and plan actions in the future that will maintai

Athira Satheesh K., K. Kamaraj, P. Sam Johnson

We present more than 50 results including some range inclusion results to characterize reverse order law for Moore-Penrose inverse of closed range Hilbert space operators. We use basic properties of Moore-Penrose inverse to prove the results. Some examples are also provided to illustrate failure cases to hold the reverse order law in infinite dimensional set

Ping-ping Wu, Zi-qiang Zhang, Xiangrong Zhu

Previous studies have indicated that the peak of the quarkonium entropy at the deconfinement transition can be related to the entropic force which would induce the dissociation of heavy quarkonium. In this paper, we study the entropic force in a rotating hot and dense medium using AdS/CFT correspondence. It turns out that the inclusion of angular velocity in